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  Visual set-up of logical models of signaling and regulatory networks with ProMoT

Saez-Rodriguez, J., Mirschel, S., Hemenway, R., Klamt, S., Gilles, E. D., & Ginkel, M. (2006). Visual set-up of logical models of signaling and regulatory networks with ProMoT. BMC Bioinformatics, 7: 506. doi:10.1186/1471-2105-7-506.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-9B11-A Version Permalink: http://hdl.handle.net/11858/00-001M-0000-002C-8A35-F
Genre: Journal Article

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eDoc_292870_2006.pdf (Publisher version), 476KB
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© 2006 Saez-Rodriguez et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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 Creators:
Saez-Rodriguez, J.1, Author              
Mirschel, S.1, Author              
Hemenway, R.1, Author              
Klamt, S.1, Author              
Gilles, E. D.1, Author              
Ginkel, Martin1, Author              
Affiliations:
1Systems Biology, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738155              

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 Abstract: Background: The analysis of biochemical networks using a logical (Boolean) description is an important approach in Systems Biology. Recently, new methods have been proposed to analyze large signaling and regulatory networks using this formalism. Even though there is a large number of tools to set up models describing biological networks using a biochemical (kinetic) formalism, however, they do not support logical models. Results: Herein we present a flexible framework for setting up large logical models in a visual manner with the software tool ProMoT. An easily extendible library, ProMoT's inherent modularity and object-oriented concept as well as adaptive visualization techniques provide a versatile environment. Both the graphical and the textual description of the logical model can be exported to different formats. Conclusion: New features of ProMoT facilitate an efficient set-up of large Boolean models of biochemical interaction networks. The modeling environment is flexible; it can easily be adapted to specific requirements, and new extensions can be introduced. ProMoT is freely available from http://www.mpi-magdeburg.mpg.de/projects/promot/.

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Language(s): eng - English
 Dates: 2006
 Publication Status: Published in print
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 Rev. Method: Peer
 Identifiers: DOI: 10.1186/1471-2105-7-506
eDoc: 292870
Other: 32/06
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Title: BMC Bioinformatics
Source Genre: Journal
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Pages: - Volume / Issue: 7 Sequence Number: 506 Start / End Page: - Identifier: -